# Browser Search

Some models on Groq have built-in support for interactive browser search, providing a more comprehensive approach to accessing real-time web content than traditional web search. Unlike [Web Search](/docs/web-search) which performs a single search and retrieves text snippets from webpages, browser search mimics human browsing behavior by navigating websites interactively, providing more detailed results.

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For latency sensitive use cases, we recommend using [Web Search](/docs/web-search) instead.

The use of this tool with a supported model or system in GroqCloud is not a HIPAA Covered Cloud Service under Groq's Business Associate Addendum at this time. This tool is also not available currently for use with regional / sovereign endpoints.

## Supported Models

Built-in browser search is supported for the following models:

| Model ID                        | Model                          |
|---------------------------------|--------------------------------|
| openai/gpt-oss-20b | [OpenAI GPT-OSS 20B](/docs/model/openai/gpt-oss-20b)
| openai/gpt-oss-120b | [OpenAI GPT-OSS 120B](/docs/model/openai/gpt-oss-120b)
| openai/gpt-oss-safeguard-20b | [OpenAI GPT-OSS-Safeguard 20B](/docs/model/openai/gpt-oss-safeguard-20b)

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**Note:** Browser search is not compatible with [structured outputs](/docs/structured-outputs).

## Quick Start

To use browser search, change the `model` parameter to one of the supported models.

When the API is called, it will use browser search to best answer the user's query. This tool call is performed on the server side, so no additional setup is required on your part to use this feature.

### Final Output

This is the final response from the model, containing snippets from the web pages that were searched, and the final response at the end. The model combines information from multiple sources to provide a comprehensive response.

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## Pricing

Please see the [Pricing](https://groq.com/pricing) page for more information.

## Best Practices

When using browser search with reasoning models, consider setting `reasoning_effort` to `low` to optimize performance and token usage. Higher reasoning effort levels can result in extended browser sessions with more comprehensive web exploration, which may consume significantly more tokens than necessary for most queries. Using `low` reasoning effort provides a good balance between search quality and efficiency.

## Provider Information

Browser search functionality is powered by [Exa](https://exa.ai/), a search engine designed for AI applications. Exa provides comprehensive web browsing capabilities that go beyond traditional search by allowing models to navigate and interact with web content in a more human-like manner.

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## Integrations: Button Group (tsx)